Development of a Web-Based System to Report Medication-Related Adverse Effects: Design and Usability Study
Notice bibliographique
Résumé
BACKGROUND: Medicine use is the most common intervention in health care. The frequency with which medicines are used means medication-related problems are very common. One common type of medication-related problems is adverse drug events, which are unintended and harmful effects associated with use of medicines. Reporting of adverse drug events to regulatory authorities is important for evaluation of safety of medicines; however, these adverse effects are frequently unreported due to various factors, including lack of consumer-friendly reporting tools. OBJECTIVE: The aim of this study was to develop a user-friendly digital tool for consumers to report medication-related adverse effects. METHODS: The project consisted of 3 parts: (1) content development, including a systematic literature search; (2) iterative system development; and (3) usability testing. The project was guided by participatory design principles, which suggest involving key stakeholders throughout the design process. The first 2 versions were developed as a mobile app and were tested with end users in 2 workshops. The third version was developed as a web application and was tested with consumers who were taking regular medicines. Consumers were asked to complete a modified version of the mHealth app usability questionnaire (MAUQ), an 18-item questionnaire with each item scored using a 7-point Likert scale ranging from 0 (strongly disagree) to 7 (strongly agree). The MAUQ assessed 3 subscales including ease of use (5 items), interface and satisfaction (7 items), and usefulness (6 items). Continuous variables were reported as mean (SD) values, whereas categorical variables were presented as frequencies (percentages). Data analysis was conducted in Microsoft Excel. RESULTS: The content for the system was based on a systematic literature search and short-listing of questions, followed by feedback from project team members and consumers. Feedback from consumers in the 2 workshops were incorporated to improve the functionality, visual design, and stability of the third (current) version. The third version of the system was tested with 26 consumers. A total of 79% (N=307/390) of all responses on the MAUQ were scored 6 or 7, indicating that users generally strongly agree with the usability of the system. When looking at the individual domains, the system had an average score of 6.3 (SD 0.9) for "ease of use," 6.3 (SD 0.8) for "interface and satisfaction," and 5.2 (SD 1.4) for "usefulness." CONCLUSIONS: The web-based system for medicine adverse effects reporting is a user-friendly tool developed using an iterative participatory design approach. Future research includes further improving the system, particularly the usefulness of the system, as well as testing the scalability and performance of the system in practice.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,024 | 0,030 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».